# IEEE Journal of Selected Topics in Signal Processing

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Displaying Results 1 - 23 of 23
• ### Front Cover

Publication Year: 2014, Page(s): C1
| PDF (224 KB)
• ### IEEE Journal of Selected Topics in Signal Processing publication information

Publication Year: 2014, Page(s): C2
| PDF (129 KB)

Publication Year: 2014, Page(s):1017 - 1018
| PDF (127 KB)
• ### Introduction to the Issue on Signal Processing in Smart Electric Power Grid

Publication Year: 2014, Page(s):1019 - 1021
Cited by:  Papers (1)
| PDF (987 KB) | HTML
• ### Distributed State Estimation and Energy Management in Smart Grids: A Consensus${+}$ Innovations Approach

Publication Year: 2014, Page(s):1022 - 1038
Cited by:  Papers (41)
| | PDF (2583 KB) | HTML

This paper reviews signal processing research for applications in the future electric power grid, commonly referred to as smart grid. Generally, it is expected that the grid of the future would differ from the current system by the increased integration of distributed generation, distributed storage, demand response, power electronics, and communications and sensing technologies. The consequence i... View full abstract»

• ### Power System Nonlinear State Estimation Using Distributed Semidefinite Programming

Publication Year: 2014, Page(s):1039 - 1050
Cited by:  Papers (16)
| | PDF (2204 KB) | HTML

State estimation (SE) is an important task allowing power networks to monitor accurately the underlying system state, which is useful for security-constrained dispatch and power system control. For nonlinear AC power systems, SE amounts to minimizing a weighted least-squares cost that is inherently nonconvex, thus giving rise to many local optima. As a result, estimators used extensively in practi... View full abstract»

• ### Power System State Estimation Under Incomplete PMU Observability—A Reduced-Order Approach

Publication Year: 2014, Page(s):1051 - 1062
Cited by:  Papers (13)
| | PDF (2760 KB) | HTML

This paper presents a state estimation method for power systems when not all state variables are observable with phasor measurement units (PMU), namely, incomplete PMU observability. Realizing that PMU measurements are generally more accurate than conventional ones, the proposed approach estimates PMU unobservable states and PMU observable states separately. The latter are estimated from PMU measu... View full abstract»

• ### Optimized Electric Vehicle Charging With Intermittent Renewable Energy Sources

Publication Year: 2014, Page(s):1063 - 1072
Cited by:  Papers (28)
| | PDF (2406 KB) | HTML

Renewable energy and Electric Vehicles (EVs) are promising solutions for energy cost savings and emission reduction. However, integration of renewable energy sources into the electric grid could be a difficult task, because of the generation source intermittency and inconsistency with energy usage. In this paper, we present results of our study on the problem of allocating energy from renewable so... View full abstract»

• ### Electric Vehicle Charging in Smart Grid: Optimality and Valley-Filling Algorithms

Publication Year: 2014, Page(s):1073 - 1083
Cited by:  Papers (19)
| | PDF (2394 KB) | HTML

Electric vehicles (EVs) offer an attractive long-term solution to reduce the dependence on fossil fuel and greenhouse gas emission. At the same time, charging a large fleet of EVs distributed across the residential area poses a challenge for the distribution network. In this paper, we formulate this problem by building on the optimal power flow (OPF) framework to model the network constraints that... View full abstract»

• ### Peak-to-Average Ratio Constrained Demand-Side Management With Consumer's Preference in Residential Smart Grid

Publication Year: 2014, Page(s):1084 - 1097
Cited by:  Papers (49)
| | PDF (3253 KB) | HTML

In a smart grid network, demand-side management plays a significant role in allowing consumers, incentivized by utilities, to manage their energy consumption. This can be done through shifting consumption to off-peak hours and thus reducing the peak-to-average ratio (PAR) of the electricity system. In this paper, we begin by proposing a demand-side energy consumption scheduling scheme for househol... View full abstract»

• ### Structure-Aware Stochastic Storage Management in Smart Grids

Publication Year: 2014, Page(s):1098 - 1110
Cited by:  Papers (8)
| | PDF (2443 KB) | HTML

Demand-side management has been proposed as an important solution for improving the energy consumption efficiency in smart grids. However, traditional pricing-based demand-side management methods usually rely on the assumption that the statistics of the system dynamics (e.g., the time-varying electricity price, the arrival distribution of consumers' demanded load) are known a priori, which does no... View full abstract»

• ### Dynamic Incentive Design for Participation in Direct Load Scheduling Programs

Publication Year: 2014, Page(s):1111 - 1126
Cited by:  Papers (8)
| | PDF (3375 KB) | HTML

Interruptible Load (IL) programs have long been an accepted measure to intelligently and reliably shed demand in case of contingencies in the power grid. However, the emerging market for Electric Vehicles (EV) and the notion of providing non-emergency ancillary services through the demand side have sparked new interest in designing direct load scheduling programs that manage the consumption of app... View full abstract»

• ### Effects of Phasor Measurement Uncertainty on Power Line Outage Detection

Publication Year: 2014, Page(s):1127 - 1139
Cited by:  Papers (8)
| | PDF (3411 KB) | HTML

Phasor measurement unit (PMU) technology provides an effective tool to enhance the wide-area monitoring systems (WAMSs) in power grids. Although extensive studies have been conducted to develop several PMU applications in power systems (e.g., state estimation, oscillation detection and control, voltage stability analysis, and line outage detection), the uncertainty aspects of PMUs have not been ad... View full abstract»

• ### Identification of Outages in Power Systems With Uncertain States and Optimal Sensor Locations

Publication Year: 2014, Page(s):1140 - 1153
Cited by:  Papers (15)
| | PDF (2930 KB) | HTML

Joint outage identification and state estimation in power systems is studied. A Bayesian framework is employed, and a Gaussian prior distribution of the states is assumed. The joint posterior of the outage hypotheses and the network states is developed in closed form, which can be applied to obtain the optimal joint detector and estimator under any given performance criterion. Employing the minimu... View full abstract»

• ### Optimal Energy Consumption Model for Smart Grid Households With Energy Storage

Publication Year: 2014, Page(s):1154 - 1166
Cited by:  Papers (7)
| | PDF (1942 KB) | HTML

In this paper, we propose to model energy consumption of smart grid households with energy storage systems as an inter-temporal trading economy. Smart homes define optimal consumption as either balancing/leveling consumption using energy storage devices such that the utility company is presented with a uniform demand or as minimizing consumption costs by storing energy during off-peak time periods... View full abstract»

• ### Real-Time Power Balancing in Electric Grids With Distributed Storage

Publication Year: 2014, Page(s):1167 - 1181
Cited by:  Papers (13)
| | PDF (3224 KB) | HTML

Power balancing is crucial for the reliability of an electric power grid. In this paper, we consider an aggregator coordinating a group of distributed storage (DS) units to provide power balancing service to a power grid through charging or discharging. We present a real-time, distributed algorithm that enables the DS units to determine their own charging or discharging amounts. The algorithm acco... View full abstract»

• ### Electricity Market Forecasting via Low-Rank Multi-Kernel Learning

Publication Year: 2014, Page(s):1182 - 1193
Cited by:  Papers (9)
| | PDF (2838 KB) | HTML

The smart grid vision entails advanced information technology and data analytics to enhance the efficiency, sustainability, and economics of the power grid infrastructure. Aligned to this end, modern statistical learning tools are leveraged here for electricity market inference. Day-ahead price forecasting is cast as a low-rank kernel learning problem. Uniquely exploiting the market clearing proce... View full abstract»

• ### Corrections to “Transform Coding Techniques in HEVC”

Publication Year: 2014, Page(s):1194 - 1195
| | PDF (209 KB) | HTML

This is a correction to the “Transform Coding Techniques in HEVC” article published in the IEEE Selected Topics in Signal Processing, vol. 7, no. 6, Dec. 2013 View full abstract»

• ### List of Reviewers

Publication Year: 2014, Page(s):1196 - 1198
| PDF (97 KB)
• ### IEEE Journal of Selected Topics in Signal Processing information for authors

Publication Year: 2014, Page(s):1199 - 1200
| PDF (137 KB)
• ### 2014 Index IEEE Journal of Selected Topics in Signal Processing Vol. 8

Publication Year: 2014, Page(s):1201 - 1216
| PDF (303 KB)
• ### IEEE Signal Processing Society Information

Publication Year: 2014, Page(s): C3
| PDF (132 KB)
• ### [Blank page - back cover]

Publication Year: 2014, Page(s): C4
| PDF (5 KB)

## Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief

Shrikanth (Shri) S. Narayanan
Viterbi School of Engineering
University of Southern California
Los Angeles, CA 90089 USA
shri@sipi.usc.edu